Example 3.9: An Infeasible Problem
This is an example of the
Infeasible Information Summary that is
displayed when an infeasible problem is encountered. Consider the
following problem:
max x + y + z + w
subject to: x +3y +2z +4w <= 5
3x + y +2z + w <= 4
5x +3y +3z +3w = 9
x, y, z, w >=0
Examination of this problem reveals that it is unsolvable.
Consequently, PROC LP identifies it as infeasible.
The following program attempts to solve it:
data infeas;
input _id_ $6. x1-x4 _type_ $ _rhs_;
datalines;
profit 1 1 1 1 max .
const1 1 3 2 4 le 5
const2 3 1 2 1 le 4
const3 5 3 3 3 eq 9
;
proc lp; run;
The results are shown in Output 3.9.1.
Output 3.9.1: The Solution of an Infeasible Problem
|
| Problem Summary |
| Objective Function |
Max profit |
| Rhs Variable |
_rhs_ |
| Type Variable |
_type_ |
| Problem Density (%) |
77.78 |
| |
|
| Variables |
Number |
| |
|
| Non-negative |
4 |
| Slack |
2 |
| |
|
| Total |
6 |
| |
|
| Constraints |
Number |
| |
|
| LE |
2 |
| EQ |
1 |
| Objective |
1 |
| |
|
| Total |
4 |
|
ERROR: Infeasible problem. Note the constraints in the constraint summary
that are identified as infeasible. If none of the constraints are
flagged then check the implicit bounds on the variables.
Output 3.9.1: (continued)
|
| Solution Summary |
Infeasible Problem |
| Objective Value |
2.25 |
| |
|
| Phase 1 Iterations |
2 |
| Phase 2 Iterations |
0 |
| Phase 3 Iterations |
0 |
| Integer Iterations |
0 |
| Integer Solutions |
0 |
| Initial Basic Feasible Variables |
4 |
| Time Used (seconds) |
0 |
| Number of Inversions |
2 |
| |
|
| Epsilon |
1E-8 |
| Infinity |
1.797693E308 |
| Maximum Phase 1 Iterations |
100 |
| Maximum Phase 2 Iterations |
100 |
| Maximum Phase 3 Iterations |
99999999 |
| Maximum Integer Iterations |
100 |
| Time Limit (seconds) |
120 |
|
Output 3.9.1: (continued)
|
| Variable Summary |
| Col |
Variable Name |
Status |
Type |
Price |
Activity |
Reduced Cost |
| 1 |
x1 |
BASIC |
NON-NEG |
1 |
0.875 |
0 |
| 2 |
x2 |
BASIC |
NON-NEG |
1 |
1.375 |
0 |
| 3 |
x3 |
ALTER |
NON-NEG |
1 |
0 |
0 |
| 4 |
x4 |
|
NON-NEG |
1 |
0 |
-0.25 |
| 5 |
const1 |
|
SLACK |
0 |
0 |
-0.25 |
| 6 |
const2 |
|
SLACK |
0 |
0 |
-0.25 |
|
Output 3.9.1: (continued)
|
| Constraint Summary |
| Row |
Constraint Name |
Type |
S/S Col |
Rhs |
Activity |
Dual Activity |
| 1 |
profit |
OBJECTVE |
. |
0 |
2.25 |
. |
| 2 |
const1 |
LE |
5 |
5 |
5 |
0.25 |
| 3 |
const2 |
LE |
6 |
4 |
4 |
0.25 |
| *INF* |
const3 |
EQ |
. |
9 |
8.5 |
0 |
|
Output 3.9.1: (continued)
|
| Infeasible Information Summary |
| Infeasible Row |
const3 |
| Constraint Activity |
8.5 |
| Row Type |
EQ |
| Rhs Data |
9 |
| Variable |
Coefficient |
Activity |
Lower Bound |
Upper Bound |
| x1 |
5 |
0.875 |
0 |
INFINITY |
| x2 |
3 |
1.375 |
0 |
INFINITY |
| x3 |
3 |
0 |
0 |
INFINITY |
| x4 |
3 |
0 |
0 |
INFINITY |
|
Note the information given in the Infeasible Information Summary for
the infeasible row CONST3.
It shows that the equality constrained
row CONST3 with right-hand-side 9 was found to
be infeasible with activity 8.5.
The summary also shows each variable that has a nonzero coefficient
in that row and its activity level at the infeasibility.
Examination of these model parameters might give you a clue as to
the cause of infeasibility, such as an incorrectly entered coefficient or
right-hand-side value.
Copyright © 1999 by SAS Institute Inc., Cary, NC, USA. All rights reserved.